Pivoted document length normalization
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Optimal aggregation algorithms for middleware
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Keyword Searching and Browsing in Databases using BANKS
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Evaluation in (XML) information retrieval: expected precision-recall with user modelling (EPRUM)
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
BLINKS: ranked keyword searches on graphs
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Discover: keyword search in relational databases
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Top-k Exploration of Query Candidates for Efficient Keyword Search on Graph-Shaped (RDF) Data
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
From keywords to semantic queries-Incremental query construction on the semantic web
Web Semantics: Science, Services and Agents on the World Wide Web
Cluster-Based Exploration for Effective Keyword Search over Semantic Datasets
ER '09 Proceedings of the 28th International Conference on Conceptual Modeling
A path-oriented RDF index for keyword search query processing
DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part II
Keyword search over RDF graphs
Proceedings of the 20th ACM international conference on Information and knowledge management
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Keyword-based search over (semi)structured data is today considered an essential feature of modern information management systems and has become an hot topic in database research and development. Most of the recent approaches to this problem refer to a general scenario where: (i) the data source is represented as a graph, (ii) answers to queries are sub-graphs of the source containing keywords from queries, and (iii) solutions are ranked according to a relevance criteria. In this paper, we illustrate a novel approach to keyword search over semantic data that combines a solution building algorithm and a ranking technique to generate the best results in the first answers generated. We show that our approach is monotonic and has a linear computational complexity, greatly reducing the complexity of the overall process. Finally, experiments demonstrate that our approach exhibits very good efficiency and effectiveness, especially with respect to competing approaches.